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Record W3090168920 · doi:10.1590/0034-7167-2019-0732

Organizational culture, authentic leadership and quality improvement in Canadian healthcare facilities

2020· article· en· W3090168920 on OpenAlexaffabout
Andréa Bernardes, Carmen Silvia Gabriel, Greta G. Cummings, Ariane Cristina Barboza Zanetti, Alexandre Bevilacqua Leoneti, Graziela Caldana, Vanessa Gomes Maziero

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsUniversity of Alberta
FundersUniversidade de São Paulo
KeywordsOrganizational cultureAccreditationAuthentic leadershipHealth careQuality managementDescriptive statisticsQuality (philosophy)PsychologyNursingMedical educationKnowledge managementBusinessPublic relationsMedicineMarketingPolitical scienceComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate relationships among flexible and hierarchical organizational cultures, quality improvement domains, and authentic leadership competencies in Canadian healthcare facilities. METHOD: Observational cross-sectional study conducted in Alberta, Canada. Nurse managers (n=226) completed a survey including validated measures of organizational culture, quality improvement and authentic leadership. Data were analyzed using descriptive statistics, Spearman's correlation coefficient and Chi-squared test (p<0.05). RESULTS: Quality improvement through accreditation is related to organizational culture and authentic leadership. We saw a propensity for participants who reported working in a more flexible culture also reported greater quality improvement implementation and authentic leadership practices. CONCLUSION: This study assessed and reported the relationships between flexible organizational cultures, quality improvement through the accreditation process, and authentic leadership practices of healthcare managers. Flexible organizational cultures influence the adoption of authentic leadership, participatory management model and also improves quality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.261
GPT teacher head0.434
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2020
Admission routes2
Has abstractyes

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